SEM Planning:The Role of the SEM Data

Team

• Will Barratt - Professor, Department of Educational Leadership• Christopher Childs – Research Analyst, Student Success • Linda Ferguson - Associate Director, Institutional Research• Tom Green – Managing Consultant, AACRAO

2013 AACRAO Strategic Enrollment Management Conference

1. Setting the stage2. Providing examples and references3. Facilitating meetings4. Developing appropriate organizational

structure5. Keeping the planning on track6. Keeping the committee members on track

The role of AACRAO SEM Consulting

ISU SEM Organization FrameworkSEM Steering Team

 

High level guidanceEnabler of cross-unit planning and action

Reviews and approves recommendations of the Councils

Student Success Council 

Development of strategic goals and assessment framework

Visions opportunities for action and improved focus of activities and energy

Supports work of Subcommittees

Recruitment Council 

Development of strategic goals and assessment framework

Visions opportunities for action and improved focus of activities and energy

Data Team 

Environmental scanningStudent enrollment behavior research

Retention and success modelingProviding data to inform planning and action

Tactical Subcommittees 

Action planning & executionTimelines and metricsActivity assessment

  

Tactical Subcommittees 

Action planning & executionTimelines and metricsActivity assessment

  

ResearchIntroductionSetting the

Stage for SEM Planning

Tracking Progress

The Role of the SEM Data Team

SEM Data Team membership

Political considerations Skill considerations Credibility considerations

Linda Ferguson – Institutional Research Jerome Cline – Institutional Research Chris Childs – Student Success Charlene Shivers – Financial Aid Deirdre Mahan – Admissions Julie Cuffle – Information Technology Tess Avelis - Registrar Will Barratt – Educational Leadership Catherine Tucker – School Counseling

SEM Data Team

ResearchIntroductionSetting the

Stage for SEM Planning

Tracking Progress

The Role of the SEM Data Team

SEM Kickoff Presentation Preparation

Environmental Scan & Enrollment Behavior• Determine content• Use pictures (graphs, charts, maps)• Engage the audience • Be able to clarify (source, timeframe,

context)

• Our charge: Describe the internal and external factors that will influence our institution’s SEM planning.

• What would you include?

Environmental Scan Purpose

• State Policy• Demographics• Preparation• Affordability• Enrollment

Environmental Scan Components

Enrollment and Retention Behavior(Tell your retention story)

• Comparison to competitors & peers• Describe differences among groups

• Income (Pell-recipients)• Type of admission• Ethnicity• Region

• Survey findings• BCSSE/NSSE• Mapworks

African American White0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

43.2%

63.2%51.6%

63.0%

1-yr Retention

20072008200920102011

Challenge: Engage the audience

What percentage of all Indiana Core40 graduates require remediation?

a) 8%b) 18%c) 28%d) 38%

General Diploma Graduates - 66% Core40 Graduates - 38% Core40 with Honors - 7%

SEM Kickoff Audience Participation

High School Graduates by Region

Source: Indiana Department of Education

Year 4 Year 4+?1 of the 2 students who don’t return after the first year transfer elsewhere

ISU Retention/Graduation

Dispelling the myths

Main 2009 6-Year Grad Rate 1st Year Retention Rate

Illinois State University 69.00% 83.00%

Ball State University 58.30% 78.00%

Central Michigan University 57.20% 77.00%

East Carolina University 56.80% 76.00%

Indiana University of Pennsylvania-Main Campus 54.20% 74.00%

University of Northern Colorado 49.30% 70.00%

Louisiana Tech University 46.40% 72.00%

The University of West Florida 45.30% 71.00%

East Tennessee State University 42.50% 67.00%

Indiana State University 40.40% 66.00%

For our type of institution, our retention rates are appropriate

Source: AACRAO SEM Consulting

Potential Retention & Graduation Peers

External and Internal analysis becomes part of the SEM Plan itself

Projected Population Change 2010 to 2050

The US Chamber of Commerce also graded states on their efficiency and cost – effectiveness.  Indiana received a “D” in this area of interest.  The issue of cost efficiency has grown in importance as frustration grows concerning the rate of tuition increases which outpace most other goods in this country (including pharmaceuticals and health care). 

Indiana did receive an “A” in the area of Policy Environment and is one of four leaders in this area: largely due to their Reaching Higher and performance-based funding initiatives. ICHE and the General Assembly will pay attention to this report card. 

Demographics

Indiana is made up of 92 counties which supply the vast majority of students to Indiana State University.  Over the next 40 years, it is projected that Indiana’s population will increase by 15% overall (Source: Indiana Business Research Center (IBRC)).1  However, over that time period it is also predicted that large swaths of mid-sized and rural communities in the North, East, and West-Central parts of Indiana will lose population.  49 of Indiana’s 92 counties are expected to see a population decline. Currently, Hamilton County is the fastest growing county in the state.  Central Indiana’s role will become more dominant - between 2010 and 2030, this region is predicted to account for 62% of the state’s total growth.  

As depicted in the chart below, Indiana’s population is getting older.  Aging baby boomers are the dominant force behind this condition.  Currently, this segment of the population accounts for about 13% of the state’s total population.  It is predicted that this segment will continue to grow through 2030, eventually representing over 20% of the state’s total population.  Other groups will continue to grow as well.  Through 2050, the college-age 

Table of Contents  

                      Page 

Executive Summary…………………………………….. 3 

Part I:  Organizing Framework…………………….. 5 

Part II:  Environmental Scan………………………… 8 

Part III:  SEM Initiatives & Strategies…………… 46 

Part IV:  Appendix – SEM Participants……….. 63 

Endnotes……………………………………………………  64 

ResearchIntroductionSetting the

Stage for SEM Planning

Tracking Progress

The Role of the SEM Data Team

Research

• Survey results• National Survey of Student Engagement• Beginning college Survey of Student Engagement• Faculty Survey of Student Engagement• Map-Works Fall Transition Survey

• Clearinghouse Data• Regression and Cluster

Student-Faculty Inter-action Scale (Means 0 

to 100)

Discussed grades or assignments with an 

instructor *

Talked about career plans with a faculty member or advisor *

Discussed ideas from your classes with fac-ulty members outside 

of class *

Worked with faculty members on activities other than course-

work **

Received prompt feedback from faculty on your academic performance

Entering Ex-pected

NaN 72 NaN 49 48 67

FY - ISU 35 51 32 20 19 47

FY - CarnClass 35.9 54 34 23 17 62

Seniors - ISU 41.8 63 41 28 24 64

Seniors - Carn-Class

43.8 63 44 30 24 70

Faculty NaN 29 23 12 68 92

5152535455565758595

Student Faculty Interactions

Students: % Often or Very Often

NSSE/BCSSE/FSSE

MapWorks ReportsBenchmark, Factors & Question Details

Our Select 6:

• Central Washington University• Eastern Kentucky University• Indiana University-Purdue University (Fort Wayne)• University of Akron• University of Southern Indiana• Western Kentucky University

MapWorks Fall Transition Survey

National Student ClearinghouseAdmits who did not enroll

Source: National Student Clearinghouse

61%19%

20%

Returned Not Enrolled

Transferred

National Student ClearinghouseFirst-time freshmen who don’t

return for second yearAll Students

77%

7%

15%

Good Standing

Returned

Not Enrolled

Transferred

What pre-college factors are related to fall to fall retention?

What during-college factors are related to fall to fall retention?◦ 2011 – 2012◦ 2012 – 2013

Cluster Analysis

What is a two-step Cluster Analysis?

A two step cluster is a way to find important characteristics that are different between two groups

Our cluster will find important characteristics that describe students who stay from the first fall semester to the second fall semester.

Finding the right variables for the Cluster: An iterative

Process 1. Focused on variables that the institution

could change2. Conducted a Binary Logistic Regression to

find variables that were predictive of retention

3. Ran several clusters and picked variables that were most important but did not overwhelm other variables in the cluster analysis

Cluster Analysis Variables

Core Demographi

cs

Pre-College Factors

First year Academic Factors

First year Co-curricular

Factors Retention

Core Demographic Variables

Gender Ethnicity Country of Origin State of Origin Zip code of Origin County of Origin Child of ISU Alumni Relative of ISU Alumni MeritSchol Type of Admission Oncampus/Offcampus ResHall MAP-Works: Fraternity or

Sorority

Family Income High School Name High School State High School County High School Zip 21st Century Scholar Military Pidm Cohort Year Pell Indicator Honors Program First Generation Indicator International Student

Pre-College Variables

High School Grad Date High School GPA High School Percentile

Rank High School Class Size ACT Test Scores SAT Test Scores SAT to ACT Composite

Application Date Hoosier Boys

State/Girls State Pre Application Hours High School Extra

Curricular Activities Summer Honors H.S Athlete

1st Year Academic Variables College Dept Major MAP-Works: Class Attendance MAP-Works: Class Participation MAP-Works: Communicate with professors

outside of class MAP-Works: Know what is expected of you to

be successful in class MAP-Works: Do family obligations interfere

with course work MAP-Works: Number of Courses taking MAP-Works: Class Participation MAP-Works: How many courses are you

struggling in Remedial Math Year 1 Indicator MAP-Works: Satisfied Academic Life MAP-Works: Do you know what is expected of

you in your classes?

Midterm Deficiencies Fall Term GPA Fall GPA Hours Took Remedial Math Took Math Took Communication 101 Freshmen Writing Visited Math Computer lab Participated in tutoring Fall Academic Standing First Year Academic Standing Three week attendance Fall Enrollment Hours Fall Attempted Hours Supplemental Instruction Attendee

1st Year Co-Curricular and other Variables

MAP-Works: Meeting people you like (peer connections)

MAP-Works: Time spent sleeping MAP-Works: Time spent socializing MAP-Works: Attend student functions MAP-Works: Communication with

parents MAP-Works: Choice of Institution MAP-Works: Commitment to ISU MAP-Works: Financial Means MAP-Works: Intramural Sports MAP-Works: Student functions MAP-Works: Volunteer MAP-Works: Leadership Position MAP-Works: Adjustment to Living on-

campus MAP-Works: How many roommates do

you have MAP-Works: Roommate Problems

MAP-Works: Satisfied with Social Life MAP-Works: Belong to a learning

community Community service Visited the Rec Center Attended ISU Performance Attended ISU Athletic Event Participated in Intramural Sports Financial Holds Student Judicial Holds Student Athlete 1st year Organization Count Organization Member African American Cultural Center

Attendance Isucceed Program indicator Spring Persistence Fall 1 to Fall 2 retention

Cluster Analysis FindingsMain Points

Participation in ISU events and student organization events were the most important variables in clusters

Cluster Analysis FindingsMain Points

Clusters indicate that students with the higher levels of student participation at ISU events and in student organizations had higher retention rates

Cluster Analysis FindingsMain Points

It may not be the events themselves that caused students to come back but factors associated with the event

• How could the first year at ISU better engage students with our expectations for them, academically?

Research Results Guiding questions

• Social engagement appears to have a strong impact on our first-year students:• What are the opportunities to leverage this to

improve their academic performance?• How can we identify and engage those students

who show greater risk for lack of social engagement, early in their first semester?

Research Results Guiding questions

ResearchIntroductionSetting the

Stage for SEM Planning

Tracking Progress

The Role of the SEM Data Team

• Purpose• Projects enrollment over the life of the SEM plan• Illustrates the impact of changes in cohort sizes and

retention rates

• Based on long-range enrollment goals• New freshman, transfer and/or graduate cohort sizes• Differential retention rates for groups within each cohort

Enrollment Model

  One-year Retention Rates    Actual Goals Fall 2012  Cohort Category Fall 2010  Fall 2011 Fall 2012 Fall 2013 Fall 2014 Fall 2015 Fall 2016 Fall 2017 ActualFirst-time, full-time bachelor's degree seekers      All  58.1% 60.6% 61.0% 63.0% 65.0% 67.0% 69.0% 70.0% 63.5%  African-American  43.2% 51.6% 52.0% 53.0% 54.0% 55.0% 56.0% 58.0% 52.5%  Pell Recipients 51.1% 56.5% 57.0% 59.0% 61.0% 63.0% 64.5% 66.0% 57.6%  21st-Century Scholars 57.1% 56.6% 58.0% 60.0% 62.0% 64.0% 66.0% 68.0% 61.2%New BDS Transfer students 64.6% 65.2% 67.0% 69.0% 71.0% 72.0% 73.0% 74.0% 67.9%

Reviewing SEM Tactical Committee plans Getting data Helping with analyses Creating a climate of data based decisions

Oversight and Monitoring

Monitoring SEM Initiatives Metric Review

  Frequency of Measurement

Reported to Whom

Expected Outcome

Data used for measurement

Location of data/system

Metric Provider Data Team Questions/Comments

Number of academic-focused student organizations

Annually AVP for Student Success & VP Student Affairs

Annual 10% increase over baseline year 

Counts of academic student organizations

Banner & OrgSync records

 Metrics

Are we going to use OrgSync or BANNER? How can we determine which are academic?   Cocurricular data in BANNER does not specify this. (See note below)

Number of students involved in residence hall living-learning communities 

Annually AVP of Student Success

Annual 10% increase in number of students involved

Counts of students involved

Department of Residential Life BANNER

Residential life This needs to be tracked and stored in BANNER and/or the data warehouse so that it can be tied to retention, performance, etc.   Can we measure the level of student engagement?  A lot of this should go into data warehouse when it is fully operational. We have definitional issues – themed floors vs living learning communities.

Monitoring SEM InitiativesProviding Metrics

Goal 1 Initiative 12C: Augment college-going education for admits

and families via multi-media tool entitled Sycamoreology

Questions and Discussion

Will Barratt - William.Barratt@indstate.eduChristopher Childs –

Christopher.Childs@indstate.eduLinda Ferguson – Linda.Ferguson@indstate.edu

Tom Green – Tom.Green@aacrao.org